Modeling mechanical milling process for synthesis of graphite nanoparticles and their characterization

Abstract

The synthesis of graphite nanoparticles at ambient temperature by high energy mechanical milling is modelled using ANN (Artificial Neural Network). The effect of milling time on the evolution of particle size, inclusion, microstructure and morphology were examined using XRD (X-Ray Diffraction), EDS (Energy Dispersive X-Ray Spectroscopy), SEM (Scanning Electron Microscope) and TEM (Transmission Electron Microscope). ANN was effectively used to predict the influence of milling time on particle size and to forecast the milling time for the formation of nanoparticles. XRD results of investigation revealed change in strain behaviour of graphite particles of different sizes when heat treated. © (2014) Trans Tech Publications, Switzerland.